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Chair of Software Engineering for Business Information Systems (sebis)
Faculty of Informatics
Technische Universität München
wwwmatthes.in.tum.de
Research and Development in BlockchainUlrich Gallersdörfer, M.Sc. – 2018, Sebis-Day
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Outline
1. Analysis of Cross-Blockchain Transactions
2. Design Patterns in Solidity
3. Current (and future) Research
© sebis180920 Gallersdoerfer Blockchain @ Sebis 2
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Transactions in Blockchains are easy to track
© sebis180920 Gallersdoerfer Blockchain @ Sebis 3© sebis 3
Tx2
From To
Tx0
From To
Tx1
From To
Tx3
From To
▪ Money in Blockchain networks (like Bitcoin or
Ethereum) are easy to track
▪ Transactions reference to previous transactions
▪ Hardly a way to hide where the money came from
▪ Mixing services (which disguise the origin of coins)
are hardly used
➔ Scam and theft still a dominant problem without a possibility to efficiently track the money
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Coins are exchanged to other currencies
© sebis180920 Gallersdoerfer Blockchain @ Sebis 4
Why are we not able to efficiently track the money? ➔ Currencies are changed into other currencies.
Trading Platforms Instant Cryptocurrency Exchange
Trading platforms are not used, as an exchange is time consuming and requires user registration.
Instant Cryptocurrency Exchanges allow a direct exchange of two currencies.
1. Is it possible to detect a transaction for a instant cryptocurrency exchange?
2. Is it possible to track the flow of money across different currencies?
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We trace cross-blockchain transactions
© sebis180920 Gallersdoerfer Blockchain @ Sebis 5
• Transaction data from two Blockchains
• Exchange Rates based on prices,
exchange fees & transaction fees
• Exchange Duration based on Timestamps
• Known Exchange Addresses
Data usage
• Very high volume (200 Mio. / month)
• High detection rate of exchange
transactions (92%)
• Correct matching very hard due to
• Many possible exchange pairs
• Over 30 cryptocurrencies
• Very small transaction amounts
• However, high volume tx traceable
Findings
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Outline
1. Analysis of Cross-Blockchain Transactions
2. Design Patterns in Solidity
3. Current (and future) Research
© sebis180920 Gallersdoerfer Blockchain @ Sebis 6
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Smart Contract Software Engineering is hard
© sebis180920 Gallersdoerfer Blockchain @ Sebis 7
Contract-based
language
Notion
of money
One single bug can
be fatal
High computational
costs
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We collected 14 different patterns
© sebis180920 Gallersdoerfer Blockchain @ Sebis 8
Behavioral
Security
Upgradeability
Economic
1. Guard Check
2. State Machine
3. Oracle
4. Randomness
5. Access Restriction / Ownable
6. Check Effects Interactions
7. Secure Ether Transfer
8. Pull over Push
9. Emergency Stop
10.Proxy Delegate
11.Eternal Storage
12.String Equality Comparison
13.Tight Variable Packing
14.Memory Array Building
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We measure the usage of these patterns
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• Increasing usage
• Doubled usage
from 10% to over
20% in only two
months
• >20% of contracts
Patterns are heavily used in Smart Contract development community!
With bytecode analysis, we are able to measure common standards.
Ownable Pattern
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Outline
1. Analysis of Cross-Blockchain Transactions
2. Design Patterns in Solidity
3. Current (and future) Research
© sebis180920 Gallersdoerfer Blockchain @ Sebis 10
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Data Analytics in Blockchain
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Ethereum Bitcoin
Public Blockchains offer rich data sets
➔Data is highly diverse: Transaction Data, User
accounts, Smart Contracts (95% Bytecode, 5%
Source Code), Flow of money
These Data allows for various analytics
➔Usage of Software Patterns (current project)
➔ Trends in Blockchain
➔Meta-services (Origin of Money, Taxes, …)
➔ If data analytics is interesting for you, talk to me.
Size
Growth
100 GB 180 GB
8Gb/Month 4Gb/Month
Tx 309 Mio. 340 Mio.
Contracts 5,6 Mio. ---
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Technische Universität München
Faculty of Informatics
Chair of Software Engineering for Business
Information Systems
Boltzmannstraße 3
85748 Garching bei München
Tel +49.89.289.
Fax +49.89.289.17136
wwwmatthes.in.tum.de
Ulrich Gallersdörfer
M.Sc.
17137
Wissenschaftlicher Mitarbeiter